Update app.py

app.py

@@ -1,10 +1,26 @@
 import gradio as gr
+import torch
+import whisper
+
+# Load the Whisper model
+model = whisper.load_model("large-v3")
+
+def transcribe(audio):
+    """Transcribes the given audio file."""
+    audio_path = audio if isinstance(audio, str) else audio.name
+    result = model.transcribe(audio_path)
+    return result["text"]
 
 with gr.Blocks(fill_height=True) as demo:
     with gr.Sidebar():
-        gr.Markdown("# Inference Provider")
-        gr.Markdown("This Space showcases the openai/whisper-large-v3 model, served by the fal-ai API. Sign in with your Hugging Face account to use this API.")
-        button = gr.LoginButton("Sign in")
-    gr.load("models/openai/whisper-large-v3", accept_token=button, provider="fal-ai")
+        gr.Markdown("# Audio Transcription")
+        gr.Markdown("This demo uses the OpenAI Whisper-large-v3 model for audio transcription.")
     
+    gr.Markdown("### Upload an audio file to transcribe")
+    audio_input = gr.Audio(source="upload", type="filepath")
+    output_text = gr.Textbox(label="Transcription")
+    transcribe_button = gr.Button("Transcribe")
+    
+    transcribe_button.click(fn=transcribe, inputs=audio_input, outputs=output_text)
+
 demo.launch()